Event Risk Calculator - Coronavirus

Estimate the probability that at least one attendee at your event is currently infectious with COVID-19, based on event size, local population, recent case counts, and an adjustable case-undercounting multiplier.

Quick Facts

Per-capita infection rate
p = (bias x cases) / population
Estimates the share of the population currently infectious.
Event risk formula
Risk = 1 - (1 - p)^n
Complement rule: chance at least one of n attendees is infected.
Undercounting
True cases are often 3-10x reported cases
Asymptomatic and untested/home-tested infections aren't in official counts.
Not medical advice
Educational estimate only
Does not model masks, ventilation, vaccination, or variants.

Your Results

Calculated
Risk at least one attendee is infected
-
Risk = 1 - (1 - p)^n
Per-capita infection rate
-
p = (bias x cases) / population
Expected infected attendees
-
n x p
Risk level
-
Rough interpretation band

Ready

Enter event size, local population, and recent case counts, then press Calculate.

How the Event Risk Calculator - Coronavirus Works

This tool estimates the probability that at least one person at a gathering is currently infectious with COVID-19, using the same underlying logic as the Georgia Tech COVID-19 Event Risk Assessment Planning Tool (Chande et al., "Real-time, interactive website for US-county-level COVID-19 event risk assessment," Nature Human Behaviour, 2020). It combines your event size with a local, per-capita estimate of active infections derived from recently reported cases and an adjustable undercounting multiplier.

The formula

First, the calculator estimates the chance that any single random person in the area is currently infectious: p = (ascertainment bias × reported cases) ÷ population. Then it applies the complement rule for independent events to estimate the chance that at least one of your n attendees is infected: Risk = 1 − (1 − p)^n. For example, with 750 reported cases over 10 days, a 5x undercount multiplier, and a population of 500,000, p ≈ 0.75%; for a 50-person event, Risk = 1 − (1 − 0.0075)^50 ≈ 31%.

Why an undercount multiplier?

Officially reported case counts miss infections that are asymptomatic, never tested, or tested at home without being reported to public health authorities. During the pandemic, researchers and health departments commonly estimated true infections at roughly 3 to 10 times the confirmed case count, depending on testing availability and reporting practices at the time. Raising the multiplier raises the estimated risk; lowering it (toward 1x) assumes reporting was close to complete.

What this calculator does not model

The result is a presence-of-infection estimate, not a transmission-risk estimate. It does not account for masking, ventilation, indoor versus outdoor settings, vaccination status, prior infection, test-to-enter policies, or the transmissibility of a specific variant — all of which materially change the actual chance of transmission at an event. It also assumes cases are evenly distributed across the population rather than clustered. Treat the output as one planning input, not a certification that an event is "safe," and consult current public health guidance and, for personal medical questions, a healthcare provider.

Frequently Asked Questions

What does the COVID-19 event risk percentage actually mean?
The risk percentage is the estimated probability that at least one currently infectious person attends your event, based on event size, local case counts, and an assumed level of case undercounting. It is not the probability that you personally will be infected, and it does not account for masks, ventilation, vaccination status, or variant infectiousness.
What is ascertainment bias and why does it matter?
Ascertainment bias is a multiplier that accounts for COVID-19 cases never officially reported, due to asymptomatic infection, limited testing, or unreported home tests. During the pandemic, researchers estimated true infections were often 3 to 10 times higher than confirmed case counts, so this calculator lets you adjust that multiplier to match current local testing conditions.
How is the risk formula derived?
The calculator estimates the per-capita chance that any one person is currently infectious as p = (ascertainment bias × active cases) ÷ population, then applies the complement rule to estimate the chance at least one of n attendees is infected: Risk = 1 − (1 − p)^n. This is the same approach popularized by the Georgia Tech COVID-19 Event Risk Assessment Planning Tool (Chande et al., Nature Human Behaviour, 2020).
Does a low percentage mean the event is safe?
No. A lower percentage means a lower estimated chance an infected person is present, but the calculator does not model transmission itself, ventilation, masking, vaccination, or indoor versus outdoor setting. Use it as one input alongside current public health guidance, not as medical advice or a safety guarantee.

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